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제목 Clinometric Gait Analysis Using Smart Insoles in Post Stroke Hemiplegia 소속 Pusan National University Hospital, Department of Rehabilitation Medicine1, Pusan National University Hospital, Biomedical Research Institute2 저자 Ra Yu Yun1*, Myung Hun Jang1, Min-seok Seo2, Myung Jun Shin1† Background
For effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient’s functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations. Gait analysis using Smart Insole technology can be applied continuously, objectively and quantitatively, thereby overcoming the shortcomings of other assessment tools.
Methods
To confirm the reliability of gait analysis using Smart Insole technology, normal healthy controls wore insoles in their shoes during the timed up-and-go (TUG) test. (Fig. 1) The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test: gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients’ clinical condition, we analyzed the relationships of 22 gait parameters on four stroke severity scales.
Results
The Smart Insole gait parameter data were similar to those calculated manually. Among the 22 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The Smart Insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the unaffected side in patients showed a markedly longer stance duration. Regarding swing duration, that of the unaffected side was shorter in patients than controls, whereas that of the affected side was longer. (Fig. 2, 3) We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the right and left sides (%) was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score. (Fig. 4)
Conclusions
This study confirmed the feasibility and applicability of the Smart Insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the Smart Insole data. Further studies are required to assess the clinical effectiveness of the Smart Insole for rehabilitation and long-term monitoring of patients with hemiplegia due to stroke.File.1: Figure 1.JPG 다운로드1Figure 1. Dividing swing / stance phase 1) The swing phase corresponded to a sum of pressure sensor value of 0, while the stance was represented by non-zero values. 2) If both sides are in Stance state, it is treated as double support. If only one side is in stance state, it is treated as single support.File.2: Figure 2.JPG 다운로드2Figure 2. Swing and stance duration distribution of affected and sound side 1) The patients showed a shorter swing duration on the sound side than the control subjects, whereas that on the affected side was longer. 2) While the patients showed a longer stance duration on both sides compared to the control subjects, the sound side showed a markedly longer duration.File.3: Figure 3.JPG 다운로드3Figure 2. Swing and stance duration distribution of affected and sound side 1) The patients showed a shorter swing duration on the sound side than the control subjects, whereas that on the affected side was longer. 2) While the patients showed a longer stance duration on both sides compared to the control subjects, the sound side showed a markedly longer duration.